shouldn't we be spending more time creating models and business logic instead of deploying code?

As data scientists, a majority of our work should be building valuable models and business logic that can drive impactful decisions. In my experience I'm either spending too much time deploying my code over a large number of computers or I'm waiting on a DevOps team to do it. I constantly feel the deployment overhead eating away at the work I SHOULD be doing and WANT to be doing. Do any of you feel the same way?

Also, if you …

building business business logic code computers data datascience data scientists decisions devops drive experience logic scientists spending waiting work